add a 2nd option for massive star enuc vis (#3188)

this uses 2 different transfer funcitons to capture the positive
and negative

also add radial velocity vis

Author: zingale

Exec/science/massive_star/analysis/vol-enuc-massivestar.py

@@ -34,6 +34,8 @@ def doit(plotfile):
     ds = CastroDataset(plotfile)
     ds._periodicity = (True, True, True)
 
+    zoom = 5
+
     t_drive = 0.0
     if "[*] castro.drive_initial_convection_tmax" in ds.parameters:
         t_drive = ds.parameters["[*] castro.drive_initial_convection_tmax"]
@@ -54,8 +56,8 @@ def doit(plotfile):
     # transfer function
     vals = [-20, -19.5, -19, -18.5, -18, -17, -16, -15, -14,
             14, 15, 16, 17, 18, 18.5, 19, 19.5, 20]
-    alpha = [0.5, 0.4, 0.4, 0.3, 0.3, 0.2, 0.2, 0.1, 0.1,
-             0.1, 0.1, 0.2, 0.2, 0.3, 0.3, 0.4, 0.4, 0.5]
+    alpha = [0.5, 0.4, 0.35, 0.3, 0.25, 0.2, 0.15, 0.1, 0.05,
+             0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.5]
     sigma = 0.1
 
     tf =  yt.ColorTransferFunction((min(vals), max(vals)))
@@ -87,10 +89,10 @@ def doit(plotfile):
 
     cam.switch_orientation(normal_vector=normal, north_vector=[0., 0., 1.])
     cam.set_width(ds.domain_width)
-    cam.zoom(5.0)
+    cam.zoom(zoom)
     sc.camera = cam
 
-    sc.save_annotated(f"{plotfile}_enuc_annotated.png",
+    sc.save_annotated(f"{plotfile}_enuc_zoom{zoom}.png",
                       label_fontsize="18",
                       label_fmt="%.1f",
                       sigma_clip=3,

Exec/science/massive_star/analysis/vol-enuc2-massivestar.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python
+
+# render a enuc using 2 separate transfer functions to better
+# show positive and negative
+
+import sys
+
+import matplotlib
+import numpy as np
+
+import yt
+from yt.frontends.boxlib.api import CastroDataset
+from yt.units import cm
+from yt.visualization.volume_rendering.api import Scene, create_volume_source
+
+matplotlib.use('agg')
+
+def _enuc_symlog(field, data):
+    f = np.log10(np.abs(data["boxlib", "enuc"]))
+    f[f < 10] = 0.0
+    return np.copysign(f, data["boxlib", "enuc"])
+
+yt.add_field(
+    name = ("boxlib", "enuc_symlog"),
+    display_name = "", #r"\mathrm{log}_{10}(\epsilon_\mathrm{nuc})~ [\mathrm{erg/g/s}]",
+    function = _enuc_symlog,
+    sampling_type = "local",
+    units = None
+)
+
+
+def doit(plotfile):
+
+    ds = CastroDataset(plotfile)
+    ds._periodicity = (True, True, True)
+
+    zoom = 1.5
+
+    t_drive = 0.0
+    if "[*] castro.drive_initial_convection_tmax" in ds.parameters:
+        t_drive = ds.parameters["[*] castro.drive_initial_convection_tmax"]
+    elif "castro.drive_initial_convection_tmax" in ds.parameters:
+        t_drive = ds.parameters["castro.drive_initial_convection_tmax"]
+    print(t_drive)
+
+    sc = Scene()
+
+    field = ("boxlib", "enuc_symlog")
+    ds._get_field_info(field).take_log = False
+
+    vals = [12, 13, 14, 15, 15.5, 16, 16.5, 17]
+    sigma = 0.15
+    alpha = [0.025, 0.05, 0.1, 0.125, 0.15, 0.2, 0.3, 0.4]
+
+    # negative values of enuc
+
+    vol2 = create_volume_source(ds.all_data(), field=field)
+    #vol2.use_ghost_zones = True
+
+    vals_r = [-v for v in reversed(vals)]
+    alpha_r = [a for a in reversed(alpha)]
+
+    cmap = "Blues_r"
+
+    tf =  yt.ColorTransferFunction((min(vals_r), max(vals_r)))
+    tf.clear()
+
+    for v, a in zip(vals_r, alpha_r):
+        tf.sample_colormap(v, sigma**2, alpha=a, colormap=cmap)
+
+    vol2.set_transfer_function(tf)
+
+    sc.add_source(vol2)
+
+    # positive values of enuc
+
+    vol = create_volume_source(ds.all_data(), field=field)
+    #vol.use_ghost_zones = True
+
+    cmap = "Reds"
+
+    tf =  yt.ColorTransferFunction((min(vals), max(vals)))
+    tf.clear()
+
+    for v, a in zip(vals, alpha):
+        tf.sample_colormap(v, sigma**2, alpha=a, colormap=cmap)
+
+    vol.set_transfer_function(tf)
+
+    sc.add_source(vol)
+
+
+    # camera
+
+    cam = sc.add_camera(ds, lens_type="perspective")
+    cam.resolution = (1920, 1280)
+
+    # view 1
+
+    cam.position = [ds.domain_right_edge[0],
+                    ds.domain_right_edge[1],
+                    ds.domain_right_edge[2]]
+
+    # look toward the center
+    center = 0.5 * (ds.domain_left_edge + ds.domain_right_edge)
+    # set the center in the vertical direction to be the height of the underlying base layer
+
+    normal = (center - cam.position)
+    normal /= np.sqrt(normal.dot(normal))
+
+    cam.switch_orientation(normal_vector=normal, north_vector=[0., 0., 1.])
+    cam.set_width(ds.domain_width)
+    cam.zoom(zoom)
+    sc.camera = cam
+
+    sc.save_annotated(f"{plotfile}_enuc_zoom{zoom}.png",
+                      label_fontsize="18",
+                      label_fmt="%.3f",
+                      sigma_clip=3,
+                      text_annotate=[[(0.05, 0.05),
+                                      f"$t - \\tau_\\mathrm{{drive}}$ = {float(ds.current_time) - t_drive:6.1f} s",
+                                      dict(horizontalalignment="left", fontsize="18")]])
+
+
+if __name__ == "__main__":
+
+    # Choose a field
+    plotfile = ""
+
+    try:
+        plotfile = sys.argv[1]
+    except:
+        sys.exit("ERROR: no plotfile specified")
+
+    doit(plotfile)

Exec/science/massive_star/analysis/vol-radvel-massivestar.py

@@ -0,0 +1,97 @@
+#!/usr/bin/env python
+
+# render the radial velocity for the massive star problem setup
+# pass in the plotfile name
+
+import sys
+
+import matplotlib
+import numpy as np
+
+import yt
+from yt.frontends.boxlib.api import CastroDataset
+from yt.units import cm
+from yt.visualization.volume_rendering.api import Scene, create_volume_source
+
+matplotlib.use('agg')
+
+
+def doit(plotfile):
+
+    ds = CastroDataset(plotfile)
+    ds._periodicity = (True, True, True)
+
+    zoom = 1.5
+
+    t_drive = 0.0
+    if "[*] castro.drive_initial_convection_tmax" in ds.parameters:
+        t_drive = ds.parameters["[*] castro.drive_initial_convection_tmax"]
+    elif "castro.drive_initial_convection_tmax" in ds.parameters:
+        t_drive = ds.parameters["castro.drive_initial_convection_tmax"]
+    print(t_drive)
+
+    sc = Scene()
+
+    field = ("boxlib", "radvel")
+    ds._get_field_info(field).take_log = False
+
+    vol = create_volume_source(ds.all_data(), field=field)
+    sc.add_source(vol)
+
+
+    # transfer function
+    vals = [-8.e7, -4.e7, -2.e7, -1.e7, 1.e7, 2.e7, 4.e7, 8.e7]
+    alpha = [0.2, 0.1, 0.05, 0.02, 0.02, 0.05, 0.1, 0.2]
+    sigma = 1.e6
+
+    tf =  yt.ColorTransferFunction((min(vals), max(vals)))
+
+    tf.clear()
+
+    cmap = "coolwarm"
+
+    for v, a in zip(vals, alpha):
+        tf.sample_colormap(v, sigma**2, alpha=a, colormap=cmap)
+
+    sc.get_source(0).transfer_function = tf
+
+    cam = sc.add_camera(ds, lens_type="perspective")
+    cam.resolution = (1920, 1280)
+
+    # view 1
+
+    cam.position = [ds.domain_right_edge[0],
+                    ds.domain_right_edge[1],
+                    ds.domain_right_edge[2]]
+
+    # look toward the center
+    center = 0.5 * (ds.domain_left_edge + ds.domain_right_edge)
+    # set the center in the vertical direction to be the height of the underlying base layer
+
+    normal = (center - cam.position)
+    normal /= np.sqrt(normal.dot(normal))
+
+    cam.switch_orientation(normal_vector=normal, north_vector=[0., 0., 1.])
+    cam.set_width(ds.domain_width)
+    cam.zoom(zoom)
+    sc.camera = cam
+
+    sc.save_annotated(f"{plotfile}_radvel_zoom{zoom}.png",
+                      label_fontsize="18",
+                      sigma_clip=5,
+                      text_annotate=[[(0.05, 0.05),
+                                      f"$t - \\tau_\\mathrm{{drive}}$ = {float(ds.current_time) - t_drive:6.1f} s",
+                                      dict(horizontalalignment="left", fontsize="18")]])
+
+
+if __name__ == "__main__":
+
+    # Choose a field
+    plotfile = ""
+
+    try:
+        plotfile = sys.argv[1]
+    except:
+        sys.exit("ERROR: no plotfile specified")
+
+    doit(plotfile)